{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Likelihood Ratio Outlier Detection with PixelCNN++\n",
    "\n",
    "## Method\n",
    "\n",
    "The outlier detector described by [Ren et al. (2019)](https://arxiv.org/abs/1906.02845) in [Likelihood Ratios for Out-of-Distribution Detection](https://arxiv.org/abs/1906.02845) uses the likelihood ratio between 2 generative models as the outlier score. One model is trained on the original data while the other is trained on a perturbed version of the dataset. This is based on the observation that the likelihood score for an instance under a generative model can be heavily affected by population level background statistics. The second generative model is therefore trained to capture the background statistics still present in the perturbed data while the semantic features have been erased by the perturbations.\n",
    "\n",
    "The perturbations are added using an independent and identical Bernoulli distribution with rate $\\mu$ which substitutes a feature with one of the other possible feature values with equal probability. For images, this means changing a pixel with a different pixel randomly sampled within the $0$ to $255$ pixel range.\n",
    "\n",
    "The generative model used in the example is a [PixelCNN++](https://arxiv.org/abs/1701.05517), adapted from the official TensorFlow Probability [implementation](https://www.tensorflow.org/probability/api_docs/python/tfp/distributions/PixelCNN), and available as a standalone model in `from alibi_detect.models.tensorflow import PixelCNN`.\n",
    "\n",
    "\n",
    "## Dataset\n",
    "\n",
    "The training set [Fashion-MNIST](https://github.com/zalandoresearch/fashion-mnist) consists of 60,000 28 by 28 grayscale images distributed over 10 classes. The classes represent items of clothing such as shirts or trousers. At test time, we want to distinguish the Fashion-MNIST test set from MNIST, which represents 28 by 28 grayscale numbers from 0 to 9."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook requires the `seaborn` package for visualization which can be installed via `pip`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ[\"TF_USE_LEGACY_KERAS\"] = \"1\"\n",
    "\n",
    "from functools import partial\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score\n",
    "import tensorflow as tf\n",
    "\n",
    "from alibi_detect.od import LLR\n",
    "from alibi_detect.models.tensorflow import PixelCNN\n",
    "from alibi_detect.utils.fetching import fetch_detector\n",
    "from alibi_detect.saving import save_detector, load_detector\n",
    "from alibi_detect.utils.tensorflow import predict_batch\n",
    "from alibi_detect.utils.visualize import plot_roc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Utility Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_data(dataset: str) -> tuple:\n",
    "    if dataset == 'mnist':\n",
    "        (X_train, y_train), (X_test, y_test) = tf.keras.datasets.mnist.load_data()\n",
    "    elif dataset == 'fashion_mnist':\n",
    "        (X_train, y_train), (X_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()\n",
    "    else:\n",
    "        raise NotImplementedError\n",
    "    X_train = X_train.astype('float32')\n",
    "    X_test = X_test.astype('float32')\n",
    "    y_train = y_train.astype('int64').reshape(-1,)\n",
    "    y_test = y_test.astype('int64').reshape(-1,)\n",
    "    if len(X_train.shape) == 3:\n",
    "        shape = (-1,) + X_train.shape[1:] + (1,)\n",
    "        X_train = X_train.reshape(shape)\n",
    "        X_test = X_test.reshape(shape)\n",
    "    return (X_train, y_train), (X_test, y_test)\n",
    "\n",
    "\n",
    "def plot_grid_img(X: np.ndarray, figsize: tuple = (10, 6)) -> None:\n",
    "    n = X.shape[0]\n",
    "    nrows = int(n**.5)\n",
    "    ncols = int(np.ceil(n / nrows))\n",
    "    fig, ax = plt.subplots(nrows=nrows, ncols=ncols, figsize=figsize)\n",
    "    n_subplot = 1\n",
    "    for r in range(nrows):\n",
    "        for c in range(ncols):\n",
    "            plt.subplot(nrows, ncols, n_subplot)\n",
    "            plt.axis('off')\n",
    "            plt.imshow(X[n_subplot-1, :, :, 0])\n",
    "            n_subplot += 1\n",
    "            \n",
    "\n",
    "def plot_grid_logp(idx: list, X: np.ndarray, logp_s: np.ndarray, \n",
    "                   logp_b: np.ndarray, figsize: tuple = (10, 6)) -> None:\n",
    "    nrows, ncols = len(idx), 4\n",
    "    fig, ax = plt.subplots(nrows=nrows, ncols=ncols, figsize=figsize)\n",
    "    n_subplot = 1\n",
    "    for r in range(nrows):\n",
    "        plt.subplot(nrows, ncols, n_subplot)\n",
    "        plt.imshow(X[idx[r], :, :, 0])\n",
    "        plt.colorbar()\n",
    "        plt.axis('off')\n",
    "        if r == 0:\n",
    "            plt.title('Image')\n",
    "        n_subplot += 1\n",
    "\n",
    "        plt.subplot(nrows, ncols, n_subplot)\n",
    "        plt.imshow(logp_s[idx[r], :, :])\n",
    "        plt.colorbar()\n",
    "        plt.axis('off')\n",
    "        if r == 0:\n",
    "            plt.title('Semantic Logp')\n",
    "        n_subplot += 1\n",
    "\n",
    "        plt.subplot(nrows, ncols, n_subplot)\n",
    "        plt.imshow(logp_b[idx[r], :, :])\n",
    "        plt.colorbar()\n",
    "        plt.axis('off')\n",
    "        if r == 0:\n",
    "            plt.title('Background Logp')\n",
    "        n_subplot += 1\n",
    "\n",
    "        plt.subplot(nrows, ncols, n_subplot)\n",
    "        plt.imshow(logp_s[idx[r], :, :] - logp_b[idx[r], :, :])\n",
    "        plt.colorbar()\n",
    "        plt.axis('off')\n",
    "        if r == 0:\n",
    "            plt.title('LLR')\n",
    "        n_subplot += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load data\n",
    "\n",
    "The in-distribution dataset is Fashion-MNIST and the out-of-distribution dataset we'd like to detect is MNIST."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(60000, 28, 28, 1) (10000, 28, 28, 1) (10000, 28, 28, 1)\n"
     ]
    }
   ],
   "source": [
    "(X_train_in, y_train_in), (X_test_in, y_test_in) = load_data('fashion_mnist')\n",
    "X_test_ood, y_test_ood = load_data('mnist')[1]\n",
    "input_shape = X_train_in.shape[1:]\n",
    "print(X_train_in.shape, X_test_in.shape, X_test_ood.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "i = 0\n",
    "plt.imshow(X_train_in[i].reshape(input_shape[:-1]))\n",
    "plt.title('Fashion-MNIST')\n",
    "plt.axis('off')\n",
    "plt.show();\n",
    "plt.imshow(X_test_ood[i].reshape(input_shape[:-1]))\n",
    "plt.title('MNIST')\n",
    "plt.axis('off')\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define PixelCNN++ model\n",
    "\n",
    "We now need to define our generative model. This is not necessary if the pretrained detector is later loaded from the Google Bucket.\n",
    "\n",
    "Key PixelCNN++ arguments in a nutshell:\n",
    "\n",
    "* *num_resnet*: number of layers ([Fig.2 PixelCNN](https://arxiv.org/abs/1606.05328)) within each hierarchical block ([Fig.2 PixelCNN++](https://arxiv.org/abs/1701.05517)).\n",
    "\n",
    "* *num_hierarchies*: number of blocks separated by expansions or contractions of dimensions. See [Fig.2 PixelCNN++](https://arxiv.org/abs/1701.05517).\n",
    "\n",
    "* *num_filters*: number of convolutional filters.\n",
    "\n",
    "* *num_logistic_mix*: number of components in the logistic mixture distribution.\n",
    "\n",
    "* *receptive_field_dims*: height and width in pixels of the receptive field above and to the left of a given pixel.\n",
    "\n",
    "Optionally, a different model can be passed to the detector with argument *model_background*. The [Likelihood Ratio paper](https://arxiv.org/abs/1906.02845) mentions that additional $L2$-regularization (*l2_weight*) for the background model could improve detection performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = PixelCNN(\n",
    "    image_shape=input_shape,\n",
    "    num_resnet=5,\n",
    "    num_hierarchies=2,\n",
    "    num_filters=32,\n",
    "    num_logistic_mix=1,\n",
    "    receptive_field_dims=(3, 3),\n",
    "    dropout_p=.3,\n",
    "    l2_weight=0.\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load or train the outlier detector\n",
    "\n",
    "We can again either fetch the pretrained detector from a [Google Cloud Bucket](https://console.cloud.google.com/storage/browser/seldon-models/alibi-detect/od/LLR/fashion_mnist) or train one from scratch:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "load_pretrained = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:alibi_detect.od.llr:No threshold level set. Need to infer threshold using `infer_threshold`.\n"
     ]
    }
   ],
   "source": [
    "filepath = os.path.join(os.getcwd(), 'my_path')  # change to download directory\n",
    "detector_type = 'outlier'\n",
    "dataset = 'fashion_mnist'\n",
    "detector_name = 'LLR'\n",
    "filepath = os.path.join(filepath, detector_name)    \n",
    "if load_pretrained:  # load pretrained outlier detector\n",
    "    od = fetch_detector(filepath, detector_type, dataset, detector_name)\n",
    "else:\n",
    "    # initialize detector\n",
    "    od = LLR(threshold=None, model=model)\n",
    "    \n",
    "    # train\n",
    "    od.fit(\n",
    "        X_train_in,\n",
    "        mutate_fn_kwargs=dict(rate=.2),\n",
    "        mutate_batch_size=1000,\n",
    "        optimizer=tf.keras.optimizers.Adam(learning_rate=1e-4),\n",
    "        epochs=20,\n",
    "        batch_size=32,\n",
    "        verbose=False\n",
    "    )\n",
    "    \n",
    "    # save the trained outlier detector\n",
    "    save_detector(od, filepath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can load our saved detector again by defining the PixelCNN architectures for the semantic and background models as well as providing the shape of the input data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:alibi_detect.od.llr:No threshold level set. Need to infer threshold using `infer_threshold`.\n"
     ]
    }
   ],
   "source": [
    "kwargs = {'dist_s': model, 'dist_b': model.copy(), 'input_shape': input_shape}\n",
    "od = load_detector(filepath, **kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's sample some instances from the semantic model to check how good our generative model is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_sample = 16\n",
    "X_sample = od.dist_s.sample(n_sample).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_grid_img(X_sample)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of the instances look like they represent the dataset well. When we do the same thing for our background model, we see that there is some background noise injected:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_sample = od.dist_b.sample(n_sample).numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_grid_img(X_sample)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare the log likelihoods\n",
    "\n",
    "Let's compare the log likelihoods of the inliers vs. the outlier data under the semantic and background models. Although MNIST data looks very distinct from Fashion-MNIST, the generative model does not distinguish well between the 2 datasets as shown by the histograms of the log likelihoods:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "shape_in, shape_ood = X_test_in.shape[0], X_test_ood.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# semantic model\n",
    "logp_s_in = predict_batch(X_test_in, od.dist_s.log_prob, batch_size=32, shape=shape_in)\n",
    "logp_s_ood = predict_batch(X_test_ood, od.dist_s.log_prob, batch_size=32, shape=shape_ood)\n",
    "logp_s = np.concatenate([logp_s_in, logp_s_ood])\n",
    "# background model\n",
    "logp_b_in = predict_batch(X_test_in, od.dist_b.log_prob, batch_size=32, shape=shape_in)\n",
    "logp_b_ood = predict_batch(X_test_ood, od.dist_b.log_prob, batch_size=32, shape=shape_ood)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show histograms\n",
    "plt.hist(logp_s_in, bins=100, label='in');\n",
    "plt.hist(logp_s_ood, bins=100, label='ood');\n",
    "plt.title('Semantic Log Probabilities')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.hist(logp_b_in, bins=100, label='in');\n",
    "plt.hist(logp_b_ood, bins=100, label='ood');\n",
    "plt.title('Background Log Probabilities')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is due to the dominance of the background which is similar (basically lots of $0$'s for both datasets). If we however take the likelihood ratio, the MNIST data are detected as outliers. And this is exactly what the outlier detector does as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "llr_in = logp_s_in - logp_b_in\n",
    "llr_ood = logp_s_ood - logp_b_ood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(llr_in, bins=100, label='in');\n",
    "plt.hist(llr_ood, bins=100, label='ood');\n",
    "plt.title('Likelihood Ratio')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Detect outliers\n",
    "\n",
    "We follow the same procedure with the outlier detector. First we need to set an outlier threshold with `infer_threshold`. We need to pass a batch of instances and specify what percentage of those we consider to be normal via `threshold_perc`. Let's assume we have a small batch of data with roughly $50$% outliers but we don't know exactly which ones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "n, frac_outlier = 500, .5\n",
    "perc_outlier = 100 * frac_outlier\n",
    "n_in, n_ood = int(n * (1 - frac_outlier)), int(n * frac_outlier)\n",
    "idx_in = np.random.choice(shape_in, size=n_in, replace=False)\n",
    "idx_ood = np.random.choice(shape_ood, size=n_ood, replace=False)\n",
    "X_threshold = np.concatenate([X_test_in[idx_in], X_test_ood[idx_ood]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New threshold: -96.67073059082031\n"
     ]
    }
   ],
   "source": [
    "od.infer_threshold(X_threshold, threshold_perc=perc_outlier, batch_size=32)\n",
    "print('New threshold: {}'.format(od.threshold))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's save the outlier detector with updated threshold:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_detector(od, filepath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now predict outliers on the combined Fashion-MNIST and MNIST datasets:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(20000, 28, 28, 1) (20000,)\n"
     ]
    }
   ],
   "source": [
    "X_test = np.concatenate([X_test_in, X_test_ood])\n",
    "y_test = np.concatenate([np.zeros(X_test_in.shape[0]), np.ones(X_test_ood.shape[0])])\n",
    "print(X_test.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "od_preds = od.predict(X_test,\n",
    "                      batch_size=32,\n",
    "                      outlier_type='instance',    # use 'feature' or 'instance' level\n",
    "                      return_feature_score=True,  # scores used to determine outliers\n",
    "                      return_instance_score=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Display results\n",
    "\n",
    "F1 score, accuracy, precision, recall and confusion matrix:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 score: 0.901 -- Accuracy: 0.901 -- Precision: 0.909 -- Recall: 0.892\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred = od_preds['data']['is_outlier']\n",
    "labels = ['normal', 'outlier']\n",
    "f1 = f1_score(y_test, y_pred)\n",
    "acc = accuracy_score(y_test, y_pred)\n",
    "prec = precision_score(y_test, y_pred)\n",
    "rec = recall_score(y_test, y_pred)\n",
    "print('F1 score: {:.3f} -- Accuracy: {:.3f} -- Precision: {:.3f} '\n",
    "      '-- Recall: {:.3f}'.format(f1, acc, prec, rec))\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "df_cm = pd.DataFrame(cm, index=labels, columns=labels)\n",
    "sns.heatmap(df_cm, annot=True, cbar=True, linewidths=.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also plot the ROC curve based on the instance level outlier scores and compare it with the likelihood of only the semantic model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "roc_data = {\n",
    "    'LLR': {'scores': od_preds['data']['instance_score'], 'labels': y_test},\n",
    "    'Likelihood': {'scores': -logp_s, 'labels': y_test}  # negative b/c outlier score\n",
    "}\n",
    "plot_roc(roc_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analyse feature scores\n",
    "\n",
    "To understand why the likelihood ratio works to detect outliers but the raw log likelihoods don't, it is helpful to look at the pixel-wise log likelihoods of both the semantic and background models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_plot = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# semantic model\n",
    "logp_fn_s = partial(od.dist_s.log_prob, return_per_feature=True)\n",
    "logp_s_pixel_in = predict_batch(X_test_in[:n_plot], logp_fn_s, batch_size=32)\n",
    "logp_s_pixel_ood = predict_batch(X_test_ood[:n_plot], logp_fn_s, batch_size=32)\n",
    "\n",
    "# background model\n",
    "logp_fn_b = partial(od.dist_b.log_prob, return_per_feature=True)\n",
    "logp_b_pixel_in = predict_batch(X_test_in[:n_plot], logp_fn_b, batch_size=32)\n",
    "logp_b_pixel_ood = predict_batch(X_test_ood[:n_plot], logp_fn_b, batch_size=32)\n",
    "\n",
    "# pixel-wise likelihood ratios\n",
    "llr_pixel_in = logp_s_pixel_in - logp_b_pixel_in\n",
    "llr_pixel_ood = logp_s_pixel_ood - logp_b_pixel_ood"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot in-distribution instances:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1008x1008 with 40 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = list(np.arange(n_plot))\n",
    "plot_grid_logp(idx, X_test_in, logp_s_pixel_in, logp_b_pixel_in, figsize=(14,14))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is clear that both the semantic and background model attach high probabilities to the background pixels. This effect is cancelled out in the likelihood ratio in the last column. The same applies to the out-of-distribution instances:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1008x1008 with 40 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = list(np.arange(n_plot))\n",
    "plot_grid_logp(idx, X_test_ood, logp_s_pixel_ood, logp_b_pixel_ood, figsize=(14,14))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
